Information visualization can be summarized as a mapping from an information space, where the information is stored, to a display space, which the user can visually explore. Existing visualization systems are described in S. G. Eick, et al., "SeeSoft--a Tool for Visualizing Line Oriented Software Statistics," IEEE Transactions on Software Engineering, vol. 18, no. 1, pp. 957-968. (November 1992); D. A. Keim, et al. "Supporting Data Mining of Large Databases by Visual Feedback Queries," Proc. of 10th International Conference on Data Engineering (February 1994); R. M. Picket and G. G. Grinstein, "Iconographic Displays for Visualizing Multidimensional Data," Proc. of IEEE Conf. on Systems, man, and Cybernetics, pp. 514-519, IEEE Press (1988) and W. S. Torgerson, "Multidimensional Scaling: Theory and Method," Psychometrika, vol. 17, pp. 201-419 (1952), hereby incorporated by reference as if fully set forth herein. These visualization systems usually provide a holistic display of the information using compact metaphors, with the goal of maximizing the amount of information to be viewed in the display space, as for example the screen of a computer monitor.
Current commercial relational database systems, such as Microsoft Access Relational Database Management System for Windows, as available from Microsoft Corp., offer little support for data visualization. Likewise, report generators, which serve as a front end to a relational database management system, using SQL to retrieve information from the database, provide limited or no functionality for segmentation or layout of the information, and essentially allow for simple presentations of subsets of a relation, e.g. using a line graph or pie chart. Examples of prior art database management systems include Business Objects, Esperant, Andyne SQL, IQ for Window and Impromptu. While these tools are useful for users who prefer to avoid SQL, they do not allow users to fully visualize relatively large data sets.
The importance of segmentation as a central operation in database exploration is emphasized in P. Selfridge et al., "IDEA: Interactive Data Exploration and Analysis," Proceedings of ACM-SIGMOD'96 pp. 24-34. The limitations of the SQL GROUP-BY operator as a segmentation facility are discussed in J. Gray, et al., "DataCube: A Relational Aggregation Operator Generalizing Group-By, Cross Tab, and Sub-Totals," Microsoft Technical Report MSR-TR-95-22 (October, 1995), hereby incorporated by reference as if fully set forth herein. Gross, et al., suggest a new operator called the Data Cube, which significantly generalizes both the GROUP-BY operator as well as the histogram, cross tabulation (also called pivot table), roll-up, drill-down and sub-total constructs found in most report generators. They also suggest several extensions to the standard set of SQL aggregate functions.
Another prior art system is the VisDB system which provides visual feedback queries for exploring large databases, described in D. A. Keim, et al, "Supporting Data Mining of Large Databases by Visual Feedback Queries," supra. The VisDB system seeks to maximize usage of the two dimensional ("2D") display screen by assigning each data item to a single pixel on the screen, and using the color and position of the pixel to indicate the relevance of the data item to the query. The VisDB system also incorporates the parallel coordinates and stick figures techniques for compact representation of large multidimensional data sets. See, for example, A. Inselberg and B. Dimsdale, "Parallel Coordinates: a Tools for Visualizing Multi-Dimensional Geometry," Proc. of Visualization '90, pp. 361-370, (1990), hereby incorporated by reference as if fully set forth herein and R. M. Picket and G. G. Grinstein, "Iconographic Displays for Visualizing Multidimensional Data," Proc. of IEEE Conf. on Systems, man, and Cybernetics, supra.
There are many systems that support visualization of a specific type of abstract data. For example, (i) TWIG as described in S. P. Reiss, "3D Visualization of Program Information" Extended Abstract and System Demonstration," hereby incorporated by reference as if fully set forth herein, is a package for visualizing programs; (ii) SeeSoft described in S. G. Eick, et al, "SeeSoft--a Tool for Visualizing Line Oriented Software Statistics," supra is a system for visualizing large software projects; and (iii) SeeNet described in R. A. Becker, et al., "Visualizing Network Data," IEEE Transactions on Visualizations and Graphics, vol. 1, no. 1, pp. 16-28 (March, 1995), hereby incorporated by reference as if fully set forth herein, is a system for visualizing connections in networks, such as the long distance telephone network. None of these systems, however, provide a general database visualization system in which any data can be explored.